Pandas DataFrame: delete a specific date in all leap years

Question

The following sequence is an excerpt from the pandas DataFrame that I have:

>>> df_t value 2011-01-31 -5.575000 2011-03-31 7.700000 2011-05-31 15.966667 2011-07-31 10.683333 2011-08-31 10.454167 2011-10-31 9.320833 2011-12-31 -0.358333 2012-01-31 -11.550000 2012-03-31 1.700000 2012-05-31 12.333333 2012-07-31 12.816667 2012-08-31 11.837500 2012-10-31 2.733333 2012-12-31 4.075000 2013-01-31 2.450000 2013-03-31 -4.262500 2013-05-31 11.491667 2013-07-31 14.812500 2013-08-31 13.920833 2013-10-31 4.125000 2013-12-31 0.075000 

How can I delete March 31st in every leap year? I tried something like:

 def isleap(year): return year % 4 == 0 and (year % 100 != 0 or year % 400 == 0) if isleap(df_t.index.year): df_t=df_t[df_t.index.dayofyear!=91] 

... but obviously it was too easy in my head. Is it the only solution to cycle through the entire data frame and check at every step, if the year is a leap year and the date is the 91st day of the year or is a simpler solution available?

EDIT: The problem is not how to determine if a year is a leap year, but if so, delete March 31st in the above frame.

Answer 1

Here is an example to do this in vector form. You should notice that and and or not suitable for a Boolean vector, use & | .

 import pandas as pd import numpy as np s = pd.Series(np.random.randn(600), index=pd.date_range('1990-01-01', periods=600, freq='M')) Out[76]: 1990-01-31 -0.7594 1990-02-28 -0.1311 1990-03-31 1.2031 1990-04-30 1.1999 1990-05-31 -2.4399 ... 2039-08-31 -0.3554 2039-09-30 -0.3265 2039-10-31 -0.3832 2039-11-30 -1.4139 2039-12-31 -0.3086 Freq: M, dtype: float64 def is_leap_and_MarchEnd(s): return (s.index.year % 4 == 0) & ((s.index.year % 100 != 0) | (s.index.year % 400 == 0)) & (s.index.month == 3) & (s.index.day == 31) mask = is_leap_and_MarchEnd(s) s[mask] Out[77]: 1992-03-31 0.7834 1996-03-31 0.3121 2000-03-31 -1.2050 2004-03-31 0.6017 2008-03-31 0.1045 ... 2020-03-31 1.1037 2024-03-31 0.5139 2028-03-31 -0.8116 2032-03-31 -0.6939 2036-03-31 -1.1999 dtype: float64 # do delete these row s[~mask]